School of Computer Information and Mathematical Sciences
M.Tech. Artificial Intelligence & Data Science
Eligibility for Admission
Passed Bachelor’s Degree or equivalent in the relevant field (B.E. / B.Tech. in CSE / IT / ECE / Software Engineering / Computer and Communication Engg. / Electronics Engineering).
Obtained at least 50% marks (45% marks in case of candidates belonging to reserved category) in the qualifying Examination.
- Admission is based on the CGPA /Percentage obtained in the UG degree and performance in the Crescent PG Entrance Exam (CPGEE)
- Applicants who have already appeared in the National level Entrance Exams like GATE, TANCET, etc., and have secured valid scores are exempted from appearing CPGEE
|Sl. No.||Name of the Programme||Tuition Fee per Semester|
|1||M.Tech. Artificial Intelligence & Data Science||Rs 40,000|
|Stipend for M.Tech. Programme|
|Rs.5000/- Per month as Stipend|
|Amenities and Service Fee – One time payment at the time of admission|
|1||Amenities and Service Fee||Rs 20,000|
|*Hostel Fee per Year|
|1||Establishment Charges||Rs 40,000/-|
|2||Boarding Charges||Rs 55,000/-|
*Amenity and Service Fee: Rs.5000/- (one time payment)
|*Transport Charges per Year (Optional)|
|1||A.C. Bus||Rs 40,000/- to 50,000/-|
*Transport charges varies based on the distance
Admission Brochure 2021-22
Programme Educational Objectives
- Applying the knowledge acquired in the Computational models , Knowledge Engineering to develop intelligent and Smart systems for the industrial problems.
- Design solutions for real world problems that involve acquiring variety of data from multiple sources using Data Science.
- Imbibing a scientific perspective to pursue research in Artificial Intelligence and Data Science using Mathematical, Engineering, and Computational tools.
On successful completion of the programme, the graduates will be able to
- Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
- Identify, formulate, research literature, and analyses complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
- Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
- Use research –based knowledge and research methods including design of experiments, analysis and interpretation of data and synthesis of the information to provide valid conclusions.
- Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
- Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
- Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
- Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
- Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
- Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
- Demonstrate knowledge and understanding of the engineering and management principles and apply these to one‟s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
- Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
Programme Specific Outcomes
- To assess, design, and implement ethical, long-term solutions in the discipline of Artificial Intelligence and Data Science
- To apply problem-solving skills and programming concepts to build a variety of solutions in an interdisciplinary domains